This invention relates to a method and system to estimate the mean frequency of a signal which has good performance over a wide range of signal-to-noise ratios and is achieved in real time.
An accurate determination of the mean frequency of a time varying signal is desired, for instance, in Doppler ultrasonic velocity measurements where the mean frequency of the signal corresponds to the mean velocity of the sampled flow field. Other applications include frequency and phase modulated communications systems and speech recognition. Acoustic measurements of blood velocity are based on the Doppler effect. Perhaps the major difficulty in these measurements is the accurate determination of the Doppler frequency shift in a noisy environment. A new time domain technique is given for determining the Doppler frequency shift which satisfies this rigid requirement.
FIG. 1 concerns a prior art implementation of time domain processing using the I/Q algorithm, so named because it derives mean frequency directly from the Doppler I (in-phase) and Q (quadrature) signals. Refer to L. Gerzberg and J. D. Meindl, "Power-Spectrum Centroid Detector for Doppler Systems Applications", Ultrasonic Imaging, Vol. 2, pp. 232-261 (July 1980). It yields results comparable to the Fourier transform technique for high S/N ratio and low frequencies, but it suffers from two major faults. The mean frequency obtained varies as the sine of the true mean frequency and there are false readings for large frequency deviations. When noise is present in the signal, the noise power appears directly in the denominator (in equation (7), P=I.sup.2 +Q.sup.2) while the noise is smoothed in the numerator. The noise factor in the denominator leads to gross errors as the S/N ratio approaches unity. The Fourier transform method has a similar form, and the noise power is estimated in order to obtain a reasonable estimate of mean frequency.